Optimal selection of the forgetting matrix into an iterative learning control algorithm by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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Content-Symmetrical Multidimensional Transpose of Image Sequences for the High Efficiency Video Coding (HEVC) All-Intra Configuration by Shanableh, Tamer

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Neural Networks as a Convex Problem by Khalil, Baha

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Complexities of special matrix multiplication problems by Takche, J.

“…This paper develops optimal algorithms to multiply an n × n symmetric tridiagonal matrix by: (i) an arbitrary n × m matrix using 2nm − m multiplications; (ii) a symmetric tridiagonal matrix using 6n − 7 multiplications; and (iii) a tridiagonal matrix using 7n −8 multiplications. …”
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On the Optimization of Band Gaps in Periodic Waveguides by Jamil Renno (14070771)

“…Five nature-inspired optimization algorithms: Genetic Algorithm (GA), Differential Evolution (DE), Grey Wolf Optimizer (GWO), Improved Grey Wolf Optimizer (IGWO), and Particle Swarm Optimization (PSO) are compared. …”

Tracking and repairing damaged healthcare databases using the matrix by Haraty, Ramzi A.

“…The algorithm is based on data dependency and uses a single matrix. …”
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Asymmetric Cryptosystem on Matrix Algebra over a Chain Ring by Muzna Yumman (16494023)

“…However, advances in quantum computers endanger the security of many asymmetric cryptosystems based on the hardness of factoring and discrete logarithm, while the complexity of the quantum algorithm makes it hard to implement in many applications. …”

Brain Source Localization in the Presence of Leadfield Perturbations by Momin, Rabiya Nakhat

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Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning by Far, Reza Davoodi

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A stochastic iterative learning control algorithm with application to an induction motor by Saab, Samer S.

“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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Stochastic P-type/D-type iterative learning control algorithms by Saab, Samer S.

“…The optimal algorithm is based on minimizing the trace of the input error covariance matrix. …”
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On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise by Saab, Samer S.

“…This paper addresses the optimality of HO-ILC in the sense of minimizing the control error covariance matrix in the presence of measurement noise. …”
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Optimality of first-order ILC among higher order ILC by Saab, Samer S.

“…That is, an optimal HO-ILC does not add to the optimality of standard first-order ILC in the sense of minimizing the trace of the control error covariance matrix. …”
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Gene selection for microarray data classification based on Gray Wolf Optimizer enhanced with TRIZ-inspired operators by Abu Zitar, Raed

“…The outcomes of the DNA microarray is a table/matrix, called gene expression data. Pattern recognition algorithms are widely applied to gene expression data to differentiate between health and cancerous patient samples. …”
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A discrete-time stochastic iterative learning control algorithm for a class of nonlinear systems by Saab, S. S.

“…This article presents a stochastic algorithm that computes the learning gain matrix of a “D-type iterative learning control (ILC) algorithm for a class of discrete-time varying nonlinear systems with linear input/output actions having relative degree one. …”
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Meta-Heuristic Algorithm-Tuned Neural Network for Breast Cancer Diagnosis Using Ultrasound Images by Ahila A (18394806)

“…The main novelty of this work is the computer-aided diagnosis scheme for detecting abnormalities in breast ultrasound images by integrating a wavelet neural network (WNN) and the grey wolf optimization (GWO) algorithm. Here, breast ultrasound (US) images are preprocessed with a sigmoid filter followed by interference-based despeckling and then by anisotropic diffusion. …”

StackDPPred: Multiclass prediction of defensin peptides using stacked ensemble learning with optimized features by Muhammad Arif (769250)

“…Additionally, we applied the local interpretable model-agnostic explanations (LIME) algorithm to understand the contribution of selected features to the overall prediction. …”

Crashworthiness optimization of composite hexagonal ring system using random forest classification and artificial neural network by Monzure-Khoda Kazi (17191207)

“…These algorithms include random forest (RF) classification and artificial neural networks (ANN). …”

Bridge Structural Health Monitoring Using Mobile Sensor Networks by Amin, Fouad

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Determining Dominant Wind Directions by Selim, S.Z.

“…Important properties of the problem are discussed and a convergent solution algorithm is designed. The algorithm could yield local optimal solutions. …”
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